TODAY’S STUDY: MANAGING CHANGE (WIND'S VARIABILITY)

The report highlighted below is a technical paper about a complicated idea but it is worth a look because it says something simple about something familiar.

Wind's enemies like to disdain it by saying it does not always blow. That's not correct. The wind is always blowing somewhere. It is also correct that the wind is variable. Predictably variable.

There is nothing wrong with variability. For human relationships, it can be the spice of life.

All sources of electricity generation are variable in predictable and unpredictable ways. Along with the rest of the world, the Japanese have just learned more than they ever wanted to know about nuclear power's unpredictable variability. During hurricane seasons, coastal residents are often reminded of the variability in the delivery of natural gas. When the stars come out at night, rooftop solar panel owners get the same reminder about sun power.

Each of these variabilities has a solution. The Japanese had a diesel engine backup system at Fukushima that might have served in a normal, short-term nuclear power plant shutdown. A transmission system can deliver electricity from inland power plants when a hurricane forces offshore natural gas supply cutoffs. Rooftop solar panel owners often have a battery storage system in the basement that sees them safely to bed.

When life gets too spicey, variability is an all too human trait that offers the opportunity to exercise understanding, patience and forgiveness on one side of the human equation and the opportunity to ask for those things and to acknowledge the blessedness of getting them on the other side.

For wind, the one side of the equation is (a) predicting fluctuations and (b)preparing for unexpectedly large-scale events. The other side of the equation is having the capability in the transmission system operator's control room (a) to exercise demand response to widely reduce electricity use and (b) to have and integrate other power sources in a timely manner.

As everyone eventually learns, everything changes but change. Working with people or wind teaches that lesson. It also teaches the greater lesson of steadiness.

Steadiness, be it with another person or in the control room of a transmission system operator, is understanding and accepting change and being prepared for it while at the same time not making it worse.

That's called managing variability.

Analysis of Wind Power Ramping Behavior in ERCOT
Yih-huei Wan, March 2011 (National Renewable Energy Laboratory)

Introduction

Texas leads the nation in terms of total wind generating capacity. Texas had more than 9,400 MW of wind power installed at the end of 2009.1 The majority of Texas’s wind power is located within the Electricity Reliability Council of Texas (ERCOT) system. The increased wind power in the electric system requires ERCOT system operators to pay more attention to the variable nature of the wind energy. From time to time, rapid changes or ramping of wind power can pose a challenge to operators to maintain grid reliability. Two such large wind ramping events—one on February 24, 20072 and one on February 26, 20083 received some media attention. This report analyzes the wind power ramping behavior using 10-minute and hourly average wind power data from ERCOT and presents statistical properties of the large ramp events. Finally, it compares these two wind ramping events with other large wind ramp events in terms of ramp duration, rate of change, and overall magnitude…

Ramping

Wind power changes constantly. Even for the aggregate wind power of a large system such as ERCOT, the power level still moves up and down in a stochastic fashion. Figure 2 is an example of the ERCOT daily wind power profile plotted with 1-minute average power.

In this example, the difference between daily maximum power and daily minimum power is over 2,100 MW. Starting at about 3,000 MW at midnight, it took about 13 hours for the wind power to decrease to around 1,100 MW. The wind power increased to about 3,300 MW four hours later. However, the long decline to daily minimum and the relatively short climb to daily maximum were not monotonic. There are smaller up and down movements with durations ranging from minutes to hours interspersed in between that create local peaks and valleys. This example points to the difficulty of objectively identifying wind power ramping events. Depending on the defining criteria of a ramp event, the starting and ending point and duration of a ramp can change substantially.

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For the electric system to operate reliably, generation must match load all the time. With wind power in the system, generation is usually managed to match the net load. In actual operations, the system must always maintain a generating capacity that is larger than the expected load to guard against the sudden loss of any generating unit. Different methods are used to balance the generation and load for different time frames. For longer time frames of days to weeks, operators will plan and commit different generating units to match the forecasted daily load profiles of weekdays and weekend. Daily load profiles can vary significantly between peak and minimum, and load profiles of weekdays and weekends can also differ substantially. Longer time is therefore needed to plan and manage the generating plants needed for load because certain generating plants need longer time from start-up to synchronizing with the load. During the day, operators routinely adjust schedules of generating units to follow the load based on system economics and updated information (e.g., weather conditions). Time frames for these operations range from hours to minutes. For still shorter time frames, the random fluctuations of load, which affect system frequency and interchange schedules, but are beyond the operators’ ability to manage, are met by automatic generation control (AGC) of the generating plants and each generating units’ governor response. Working together, AGC and governor response rapidly changes the output of generating units to match load in real time.

It is clear that the variability of wind power affects the system operations. This analysis will concentrate on the large wind-power ramping events that could affect system operations in the sub-hourly and hourly time frames. The original 1-minute wind power time-series data are processed into 10-minute average power time-series data and hourly average power time-series data. The 10-minute and hourly time-series data are used to investigate wind power ramping events…

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Ramping Rate

Analysis of the ramp events shows that the largest of such events can result in wind power level changes in thousands of MW (more than 50% of the total wind power capacity) in 9 or 10 hours. Such events, although massive in terms of net power level changes, usually do not result in very high rates of change because they took more hours to complete. The equivalent ramping rates (in both MW per hour and percentage of total wind capacity per hour) of the largest ramp events for each year (listed in Table 2) are shown in Table 8. The largest down ramp event occurred on June 9, 2008, when wind power dropped 4,211 MW in 9 hours. This event resulted in an average rate of -468 MW per hour, or about 5.8% of the total wind capacity per hour. Moving down on the time steps, it is equivalent to less than 1% per 10 minutes, which is not a severe event. However, the actual sub-hourly ramping rate can be much higher. For example, Table 1 shows the maximum hourly step change is 2,382 MW, or 26.6% of the total wind capacity in an hour. It is equivalent to 397 MW or 4.5% per 10-minute period. To investigate the sub-hourly ramping rate, 10-minute wind power time-series data are used because the hourly averaging process smoothed out the fast, sub-hourly fluctuations…

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Apparent Effect of Wind Power on System Net Load

Wind power in ERCOT has not been actively controlled by system operators to follow the load or track a fixed schedule. One way to gauge the effect of large amounts of wind power on system operations is to analyze the fluctuations of the net load, i.e., load minus wind power, and compare it to how the load would fluctuate if there is no wind power.

Changes of wind power level from one period to the next are independent of changes of load level from one period to the next. If the changes are in the same direction, i.e., both increase or decrease at the same period, the effect is less change on other generators that are used to follow the load. If the load and wind power changes are in opposite directions, it will require more change for other generators. Figure 7 is a scatter plot of load and wind step changes using 2008 hourly data…

It should be noted that this analysis applies to shorter term fluctuations of wind power and system load. There is no reason to think the change of wind power from one 10-minute period to the next with cause the system load to change in the same (or opposite) direction during the same 10-minute periods, and the available data support it. The correlation coefficient of the 10-minute wind power change and load change for 2009 was -0.05. Figure 7 showed that there were slightly more incidences of wind power and load moving in opposite directions than in the same direction.

Longer term wind power profiles such as daily and seasonal patterns are not random, and its effects on system net load are easier to predict. Figure 8 shows average daily wind power profiles for 2009 by month. It can be seen that for the most part the installed wind power capacity will produce a daily profile that is opposite to the typical daily profile of the system load, especially during summer months of May through September. Although traces in Figure 8 are based on hourly average valued over an entire month, its shapes still suggest that large down ramps tend to start in the early morning hours and large up ramps tend to start in the afternoon hours as discussed in section 3.2 of this report…

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Event on February 24, 2007

On February 24, 2007, starting at approximately 9:00 in the morning, wind power in the ERCOT area began to drop at a rate of 624 MW/h. The precipitous drop continued for about two hours and thirty minutes for a loss of 1,560 MW of wind power. This amount represents 36% of total installed wind capacity for 2007 and 45% of the highest coincidental-peak wind generation during 2007. Figure 10 below shows the wind power profile of that day. This drop of wind power coincided with the ERCOT morning load pick up of that day (a Saturday). ERCOT needed to initiate Step 1 of the Emergency Electrical Curtailment Plan (EECP) for 32 minutes because of the low Adjusted Responsive Reserve (ARR) and violation of Control Performance Standard 1 (CPS1).

This down ramp of wind power was the most severe case in 2007, although neither its magnitude (-1,560 MW) nor its down ramp rate (624 MW/h) by itself was the worst for 2007. There were much larger changes in magnitude of -3,116 MW (but it took 9 hours), and higher down ramp rates of -1,235 MW/h (in an hour) and -631 MW/h (in 2 hours). This event’s high ramp rate with a somewhat longer duration (2.5 hours) made it the most severe case in 2007. The drop of wind power was the result of very high wind in west Texas that caused the wind turbines to shut down. The load picked up at about 1,000 MW/h that morning, which was actually much greater than the highest up wind-ramp rates in the entire 2007. The ERCOT report did include other factors such as load changes in steel mills and slow response by other generating units at low load levels that contributed to ERCOT’s action of entering Step 1 of EECP. It should be noted that this event resulted in no loss of load, which is the ultimate goal of system reliability.

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Event on February 26, 2008

On February 26, 2008, starting at approximately 10:20 in the morning, wind power in the ERCOT system reached its peak of that day of 2,650 MW and started to drop. The down ramp started a slow pace of 189 MW/h and quickened to 395 MW/h after 14:00 in the afternoon. The down ramp continued until 22:00 in the night when there were only about 64 MW of wind power. The long wind power down-ramp coincided with ERCOT’s evening load pick up (after 15:10 at a rate of 2,500 MW/h) of the day. Coupled with a trip of one conventional generating unit, ERCOT entered Step 1 and Step 2 of EECP due to low ARR. Total wind power drop in 10.8 hours was 2,586 MW, which was 55% of the highest coincident-peak wind generation in 2008. In terms of total installed wind capacity for 2008, it was only 34%. The average rate of this down ramp event was -239 MW/h with a peak rate of -395 MW/h. Figure 11 shows the 1-minute and hourly wind profiles of the day.

Unlike the event of February 24, 2007, this ramp event was not the worst case in 2008. On November 11, 2008, wind power in the ERCOT system dropped 3,430 MW in 10.8 hours. This down ramp rate was not the most severe either. For all down ramp events in the 11-hour duration group, the highest down ramp rate was -431 MW/h (see Table 9). In terms of ramp magnitude, this event ranked 7th for all down ramps in the 11-hour duration group and 53rd of all down ramp events in 2008. Its average down ramp rate of -239 MW/h ranked 8th among all down ramps in the 11-hour duration group. Even the highest down rate of this event is less than the maximum down ramp rate of -431 MW/h (itself an average rate) in the 11-hour duration group. There were two other factors that contributed to ERCOT’s action of entering Steps 1 and 2 of EECP; the unexpected loss of a conventional generator and a quicker than forecasted evening load pick-up.14 Again, no loss of firm load resulted from this event.

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Conclusions

The data has shown that large wind power ramping events occurred often. A relatively large ramp with a magnitude of at least 25% of total wind power capacity will occur about once every other day. As the installed wind generation continues to increase, very large ramp events with a magnitude of 50% of total wind capacity actually decrease. In terms of actual peak wind generation, the numbers of very large ramp events (those with a magnitude greater that 50% of the peak wind generation) stay at a fairly constant frequency of about once every week. The majority of up ramp events started in the afternoon hours and the majority of down ramp events started in the morning hours. In addition, very large ramp events tend to occur in the winter months as well-defined weather fronts in these months affect large numbers of wind turbines in the same time period.

None of the large ramping events identified from the available data had a ramping rate greater than 10% of the wind generating capacity per minute. Individual wind plants can ramp faster than 10% of its capacity per minute under certain wind conditions, but when aggregating this much wind generating capacity over a wind area as is the case in ERCOT, the combined output does not have a high ramping rate that exceeds 10% of the capacity per minute.

Because the system load is still much larger than the actual production of wind power in ERCOT system, load fluctuations still dominate the overall net load fluctuations. Wind power only increases the net load σ 4-5% over the σ of load alone. The two widely reported wind ramp-events in ERCOT were not the most severe ramp events in terms of overall magnitude and ramping rates. There were much more severe down ramp events in ERCOT that did not result in reportable events for ERCOT grid operators. This suggests that for a system as large as ERCOT, the current level of wind power penetration is not likely to cause reportable events, even for very large wind ramp-events. Only when other unforeseeable incidents such as large errors in forecasting load and forced outages of conventional generators that aggravate the situation will a large wind ramp become a problem for grid operators. This is not to say that large wind ramps are of no concerns to grid operators. However, as operators gain more experience with large wind ramps and with better wind ramp forecasting, their ability to cope with such events will improve.